Zheng Yuxin, Zhang Yajiao, Chen Liyu, Lu Kefeng, Liu Junping, Lou Jiangyan
Second Clinical College, Zhejiang University of Traditional Chinese Medicine, Hangzhou, China.
Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou, China.
Gland Surg. 2024 Jun 30;13(6):812-824. doi: 10.21037/gs-23-492. Epub 2024 Jun 27.
The most common metastatic site of follicular variant of papillary thyroid carcinoma (FVPTC) is the central lymph nodes, which may be associated with the prognosis and survival of patients. In the present study, we establish a combined model based on preoperative clinical and ultrasound (US) features of FVPTC to predict the risk of central lymph node metastasis (CLNM).
From January 2013 to December 2022, 315 patients with FVPTC were enrolled and randomly divided into the training and validation cohorts in a ratio of 7:3. The independent risk factors for CLNM in FVPTC were analysed using univariate and multivariate logistic regression analyses. Then, three different models were established based on clinical and US data. Subsequently, a nomogram was constructed to predict CLNM. Its predictive effect was evaluated via receiver operating characteristic and calibration curve analyses.
Backward multivariate regression analysis revealed that age (P=0.001), thyroid peroxidase antibody (TPOAb) (P=0.11), diameter (P=0.047), irregular/lobulated margin (P=0.15), extrathyroidal extension (P=0.001), nodules with macrocalcifications (P=0.009), nodules with microcalcification (P=0.003) and Thyroid Imaging Reporting and Data System (ACR-TI-RADS) category 5 (P=0.33) were independent risk factors for CLNM in FVPTC. The areas under the curve of the matching nomogram in the training (N=221) and validation cohorts (N=94) were 0.841 [95% confidence interval (CI): 0.788-0.895] and 0.735 (95% CI: 0.621-0.872), respectively.
Preoperative thyroid US provides useful features for prediction of CLNM. The nomogram constructed based on combining US and clinical features can better predict the risk of CLNM and may facilitate decision-making in clinical settings.
甲状腺乳头状癌滤泡变体（FVPTC）最常见的转移部位是中央淋巴结，这可能与患者的预后和生存相关。在本研究中，我们基于FVPTC的术前临床和超声（US）特征建立了一个联合模型，以预测中央淋巴结转移（CLNM）的风险。
2013年1月至2022年12月，纳入315例FVPTC患者，并按7:3的比例随机分为训练队列和验证队列。采用单因素和多因素逻辑回归分析FVPTC中CLNM的独立危险因素。然后，基于临床和超声数据建立了三种不同的模型。随后，构建列线图以预测CLNM。通过受试者工作特征曲线和校准曲线分析评估其预测效果。
向后多因素回归分析显示，年龄（P=0.001）、甲状腺过氧化物酶抗体（TPOAb）（P=0.11）、直径（P=0.047）、边缘不规则/分叶状（P=0.15）、甲状腺外侵犯（P=0.001）、有粗大钙化的结节（P=0.009）、有微钙化的结节（P=0.003）和美国放射学会甲状腺影像报告和数据系统（ACR-TI-RADS）5类（P=0.33）是FVPTC中CLNM的独立危险因素。训练队列（N=221）和验证队列（N=94）中匹配列线图的曲线下面积分别为0.841 [95%置信区间（CI）：0.788-0.895]和0.735（95%CI：0.621-0.872）。
术前甲状腺超声为预测CLNM提供了有用的特征。基于超声和临床特征相结合构建的列线图可以更好地预测CLNM的风险，并可能有助于临床决策。
